pandas.CategoricalIndex¶
-
class
pandas.
CategoricalIndex
[source]¶ Index based on an underlying
Categorical
.CategoricalIndex, like Categorical, can only take on a limited, and usually fixed, number of possible values (categories). Also, like Categorical, it might have an order, but numerical operations (additions, divisions, …) are not possible.
Parameters: - data : array-like (1-dimensional)
The values of the categorical. If categories are given, values not in categories will be replaced with NaN.
- categories : index-like, optional
The categories for the categorical. Items need to be unique. If the categories are not given here (and also not in dtype), they will be inferred from the data.
- ordered : bool, optional
Whether or not this categorical is treated as an ordered categorical. If not given here or in dtype, the resulting categorical will be unordered.
- dtype : CategoricalDtype or the string “category”, optional
If
CategoricalDtype
, cannot be used together with categories or ordered.New in version 0.21.0.
- copy : bool, default False
Make a copy of input ndarray.
- name : object, optional
Name to be stored in the index.
Raises: - ValueError
If the categories do not validate.
- TypeError
If an explicit
ordered=True
is given but no categories and the values are not sortable.
See also
Index
- The base pandas Index type.
Categorical
- A categorical array.
CategoricalDtype
- Type for categorical data.
Notes
See the user guide for more.
Examples
>>> pd.CategoricalIndex(['a', 'b', 'c', 'a', 'b', 'c']) CategoricalIndex(['a', 'b', 'c', 'a', 'b', 'c'], categories=['a', 'b', 'c'], ordered=False, dtype='category') # noqa
CategoricalIndex
can also be instantiated from aCategorical
:>>> c = pd.Categorical(['a', 'b', 'c', 'a', 'b', 'c']) >>> pd.CategoricalIndex(c) CategoricalIndex(['a', 'b', 'c', 'a', 'b', 'c'], categories=['a', 'b', 'c'], ordered=False, dtype='category') # noqa
Ordered
CategoricalIndex
can have a min and max value.>>> ci = pd.CategoricalIndex(['a','b','c','a','b','c'], ordered=True, ... categories=['c', 'b', 'a']) >>> ci CategoricalIndex(['a', 'b', 'c', 'a', 'b', 'c'], categories=['c', 'b', 'a'], ordered=True, dtype='category') # noqa >>> ci.min() 'c'
Attributes
codes categories ordered Methods
rename_categories
(self, \*args, \*\*kwargs)Rename categories. reorder_categories
(self, \*args, \*\*kwargs)Reorder categories as specified in new_categories. add_categories
(self, \*args, \*\*kwargs)Add new categories. remove_categories
(self, \*args, \*\*kwargs)Remove the specified categories. remove_unused_categories
(self, \*args, …)Remove categories which are not used. set_categories
(self, \*args, \*\*kwargs)Set the categories to the specified new_categories. as_ordered
(self, \*args, \*\*kwargs)Set the Categorical to be ordered. as_unordered
(self, \*args, \*\*kwargs)Set the Categorical to be unordered. map
(self, mapper)Map values using input correspondence (a dict, Series, or function).